Publications
A quantile-based encoder-decoder framework for multi-step ahead runoff forecasting. Journal of Hydrology, 619, 129269. Retrieved from https://www.sciencedirect.com/science/article/pii/S0022169423002111
. (2023). Investigating the impact of input variable selection on daily solar radiation prediction accuracy using data-driven models: a case study in northern Iran. Stochastic Environmental Research and Risk Assessment, 36(1), 225-249. Retrieved from https://link.springer.com/article/10.1007/s00477-021-02070-5
. (2022). Improving hydrological forecasts through temporal hierarchal reconciliation. EGU General Assembly 2021. Retrieved from https://meetingorganizer.copernicus.org/EGU21/EGU21-13303.html
. (2021). Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS. Expert systems with applications, 41, 5267–5276. Elsevier.
. (2014). On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction. Agricultural and Forest Meteorology, 278, 107647. Elsevier.
. (2019). Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle. Environmental research, 155, 141–166. Academic Press.
. (2017). Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model. Stochastic environmental research and risk assessment, 31, 1211–1240. Springer Berlin Heidelberg.
. (2017). The application of dynamic linear bayesian models in hydrological forecasting: varying coefficient regression and discount weighted regression. Journal of Hydrology, 530, 762–784. Elsevier.
. (2015). Data assimilation for streamflow forecasting using extreme learning machines. Water Resources Research, 56, e2019WR026226.
. (2020). Hydrological data assimilation using Extreme Learning Machines. In EGU General Assembly Conference Abstracts (Vol. 19, p. 5722).
. (2017). Coupling machine learning methods with wavelet transforms and the bootstrap and boosting ensemble approaches for drought prediction. Atmospheric research, 172, 37–47. Elsevier.
. (2016). Forecasting drought via bootstrap and machine learning methods. In CSCE 3rd Specialty Conference on Disaster Prevention and Mitigation.
. (2013). Improving Deep Learning hydrological time series modeling using Gaussian Filter preprocessing. EGU General Assembly 2021. Retrieved from https://meetingorganizer.copernicus.org/EGU21/EGU21-1644.html
. (2021). Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models. Journal of Hydrology, 598, 126370. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S0022169421004170
. (2021). Using a boundary-corrected wavelet transform coupled with machine learning and hybrid deep learning approaches for multi-step water level forecasting in Lakes Michigan and Ontario. EGU General Assembly Conference Abstracts, 4233. Retrieved from https://scholar.google.ca/scholar?oi=bibs&cluster=8698411343122623888&btnI=1&hl=en
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